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Dynamic sensory probabilistic maps for mobile robot localization

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dc.contributor.author Vlassis, NA en
dc.contributor.author Papakonstantinou, G en
dc.contributor.author Tsanakas, P en
dc.date.accessioned 2014-03-01T02:41:32Z
dc.date.available 2014-03-01T02:41:32Z
dc.date.issued 1998 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/30516
dc.subject Dynamic Environment en
dc.subject Mobile Robot en
dc.subject Mobile Robot Localization en
dc.subject Position Estimation en
dc.subject Probability Density Function en
dc.subject Robot Localization en
dc.subject Sensor Model en
dc.subject Structural Change en
dc.subject.other Algorithms en
dc.subject.other Mathematical models en
dc.subject.other Mobile robots en
dc.subject.other Motion planning en
dc.subject.other Probability density function en
dc.subject.other Sensor data fusion en
dc.subject.other Dynamic sensory probabilistic maps en
dc.subject.other Mobile robot localization en
dc.subject.other Intelligent robots en
dc.title Dynamic sensory probabilistic maps for mobile robot localization en
heal.type conferenceItem en
heal.identifier.primary 10.1109/IROS.1998.727276 en
heal.identifier.secondary http://dx.doi.org/10.1109/IROS.1998.727276 en
heal.publicationDate 1998 en
heal.abstract In order to localize itself, a mobile robot tries to match its sensory information at any instant against a prior environment model, the map. A probabilistic map can be regarded as a model that stores at each robot configuration q the probability density function of the sensor readings at q. By combining the knowledge of its current position, the new-coming sensory information, and the probabilistic map the robot is capable of improving its prior position estimate. In this paper we propose a novel sensor model and a method for maintaining a probabilistic map in cases of dynamic environments. When the environment structure changes, the map must adapt to this change by modifying the sensor densities at the respective configurations. We propose a combined algorithm for map update and robot localization. en
heal.publisher IEEE, Piscataway, NJ, United States en
heal.journalName IEEE International Conference on Intelligent Robots and Systems en
dc.identifier.doi 10.1109/IROS.1998.727276 en
dc.identifier.volume 2 en
dc.identifier.spage 718 en
dc.identifier.epage 723 en


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